This course will provide you with an overview over existing data products and a good understanding of the data collection landscape. With the help of various examples you will learn how to identify which data sources likely matches your research question, how to turn your research question into measurable pieces, and how to think about an analysis plan. Furthermore this course will provide you with a general framework that allows you to not only understand each step required for a successful data collection and analysis, but also help you to identify errors associated with different data sources. You will learn some metrics to quantify each potential error, and thus you will have tools at hand to describe the quality of a data source. Finally we will introduce different large scale data collection efforts done by private industry and government agencies, and review the learned concepts through these examples. This course is suitable for beginners as well as those that know about one particular data source, but not others, and are looking for a general framework to evaluate data products.

KM

The teacher for the course was great. She explained everything very clearly. She also explained what is coming next. Learned a lot. Reading materials were overwhelming.

AM

Aug 23, 2017

Filled StarFilled StarFilled StarFilled StarFilled Star

This great course and a good foundation for the specialization. The lecturer is amazing and experienced. I really enjoyed this one.

À partir de la leçon

Application of TSE Framework to Existing Surveys

In this module we introduce a few surveys across a variety of topics. For each we highlight data collection features. The surveys span a variety of topics. We challenge you to think about alternative data sources that can be used to gather the same information or insights.

Enseigné par

Frauke Kreuter, Ph.D.

Professor, Joint Program in Survey Methodology

Mariel Leonard

Lecturer

Transcription

The fifth survey is the Behavioral Risk Factors Surveillance Survey, BRFSS. Some call it BRFSS. It's purpose is to provide state level heath measures and risk-related behaviors. And it writes estimates of state's health, public health officials. And again, interest here not just the current state but measurement over time. So consistency is important. Interesting here, I'll come to that in a second. This is done slightly differently from state to state. So while there is a lot of comparison going on of these survey data across the different states, you really want to look closely on how the measurement of health is done in each of them. The term population is defined the same in the US with adults in households. Ran in the dawn survey again. Repeated cross section like we had before, so no panel. And a telephone interview using interviewers. Here's a snippet of the questionnaire, just like we had for the other surveys, and some example for data reports from this particular survey. You find those, and many more results, on the CDC website. The design issues, as I alluded to earlier, are really interesting for the BRFSS because it's very difficult to standardize the data collection across all the different states. The data collection agencies do this very differently. One example. Some have interviewers that do nothing but the DRFSS and they run thousands of interviews on that same questionaire. Now just imagine how you would administer a question if you asked it for the five hundredth time. So, there might be some interviewer effects, and you'll learn more about these in subsequent courses. But that's only one of them. Here too you have the issue of balancing innovation and measurement and the change over time. And an increasing nonresponse rate, because people don't participate in the surveys. Now Google Search has tried to put out alternative indicators like Google Food Trend. Search keys, search terms on the website and algorithms that relate those to key indicators collected by CDC. It's not unlikely that some of the measures in the BRFSS would be replaced by those kind of data collection efforts.